* Add early stopping patience and minimum threshold metric must improve to prevent early stopping to pytorch trainer
* Add early stopping test
* Set patience counter to 0 if best metric not defined yet
* Make early stopping a callback. Add callback event for updating the best metric for early stopping callback to trigger on.
* Run make style
* make funciton name sensible
* Improve new argument docstring wording and hope that flakey CI test passes.
* Use on_evaluation callback instead of custom. Remove some debug printing
* Move early stopping arguments and state into early stopping callback
* Run make style
* Remove old code
* Fix docs formatting. make style went rogue on me.
* Remove copied attributes and fix variable
* Add assertions on training arguments instead of mutating them. Move comment out of public docs.
* Make separate test for early stopping callback. Add test of invalid arguments.
* Run make style... I remembered before CI this time!
* appease flake8
* Add EarlyStoppingCallback to callback docs
* Make docstring EarlyStoppingCallabck match other callbacks.
* Fix typo in docs
* Make ci fail
* Try to make tests actually run?
* CI finally failing?
* Fix CI
* Revert "Fix CI"
This reverts commit ca7923be73.
* Ooops wrong one
* one more try
* Ok ok let's move this elsewhere
* Alternative to globals() (#8667)
* Alternative to globals()
* Error is raised later so return None
* Sentencepiece not installed make some tokenizers None
* Apply Lysandre wisdom
* Slightly clearer comment?
cc @sgugger
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* [model_cards]: control arabic model examples
* [model_cards]: control input examples of Geotrend models
* [model_cards]: add link to generatation script
* replace init_ddp_connection for index init
* style
* add finetune test
* add test data
* move generate tensors to device
* add test on EM metric
* style
* allow multi process test
* keep gloo process group for retrieval
* add multi-gpu test
* use custom accelerator
* clean test finetune
* minor
* style
* style
* typo
* use python call instead of imported main fumction
* return_dict fix in modeling_rag
* use float32 in retrieval
* store as float32 as well in the custom knowledge dataset example
* style
* rename to finetune_rag
* style
* update readme
* rename utils and callbacks to utils_rag and callbacks_rag
* fix test
* patrick's comments
* generate dummy data in the finetue test script
* remove dummy data files
* style
You may be unaware but you're running some software that meddles with every commit on https://github.com/huggingface/transformers/
Something is wrong with the software you're using. It adds a reference to almost every PR in the master tree. Which is very wrong. Please check your software and please don't do it again.
Example:
see the bottom of this PR and most other PRs:
https://github.com/huggingface/transformers/pull/8639
* `disable_ngram_loss` fix for prophetnet
* add changes documentation
* fix _compute_loss to use mean reduction and -100 to masked tokens & remove unnecessary arguments
* mean label smoothing loss
* small refactor
* fix test
Co-authored-by: patrickvonplaten <patrick.v.platen@gmail.com>
* working on LongformerForSequenceClassification
* add TFLongformerForMultipleChoice
* add TFLongformerForTokenClassification
* use add_start_docstrings_to_model_forward
* test TFLongformerForSequenceClassification
* test TFLongformerForMultipleChoice
* test TFLongformerForTokenClassification
* remove test from repo
* add test and doc for TFLongformerForSequenceClassification, TFLongformerForTokenClassification, TFLongformerForMultipleChoice
* add requested classes to modeling_tf_auto.py
update dummy_tf_objects
fix tests
fix bugs in requested classes
* pass all tests except test_inputs_embeds
* sync with master
* pass all tests except test_inputs_embeds
* pass all tests
* pass all tests
* work on test_inputs_embeds
* fix style and quality
* make multi choice work
* fix TFLongformerForTokenClassification signature
* fix TFLongformerForMultipleChoice, TFLongformerForSequenceClassification signature
* fix mult choice
* fix mc hint
* fix input embeds
* fix input embeds
* refactor input embeds
* fix copy issue
* apply sylvains changes and clean more
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Updated the Extractive Question Answering code snippets
The Extractive Question Answering code snippets do not work anymore since the models return task-specific output objects. This commit fixes the pytorch and tensorflow examples but adding `.values()` to the model call.
* Update task_summary.rst
